Tetralol derivative NNC-55-0396 targets hypoxic cells in the glioblastoma microenvironment: an organ-on-chip approach.

Glioblastoma (GBM) is a highly malignant brain tumour characterised by limited treatment options and poor prognosis. The tumour microenvironment, particularly the central hypoxic region of the tumour, is known to play a pivotal role in GBM progression. Cells within this region adapt to hypoxia by stabilising transcription factor HIF1-α, which promotes cell proliferation, dedifferentiation and chemoresistance. In this study we sought to examine the effects of NNC-55-0396, a tetralol compound which overactivates the unfolded protein response inducing apoptosis, using the organ-on-chip technology. We identified an increased sensitivity of the hypoxic core of the chip to NNC, which correlates with decreasing levels of HIF1-α in vitro. Moreover, NNC blocks the macroautophagic process that is unleashed by hypoxia as revealed by increased levels of autophagosomal constituent LC3-II and autophagy chaperone p62/SQSTM1. The specific effects of NNC in the hypoxic microenvironment unveil additional anti-cancer abilities of this compound and further support investigations on its use in combined therapies against GBM.

Surface modifications of COP-based microfluidic devices for improved immobilisation of hydrogel proteins: long-term 3D culture with contractile cell types and ischaemia model.

The tissue microenvironment plays a crucial role in tissue homeostasis and disease progression. However, the in vitro simulation has been limited by the lack of adequate biomimetic models in the last decades. Thanks to the advent of microfluidic technology for cell culture applications, these complex microenvironments can be recreated by combining hydrogels, cells and microfluidic devices. Nevertheless, this advance has several limitations. When cultured in three-dimensional (3D) hydrogels inside microfluidic devices, contractile cells may exert forces that eventually collapse the 3D structure. Disrupting the compartmentalisation creates an obstacle to long-term or highly cell-concentrated assays, which are extremely relevant for multiple applications such as fibrosis or ischaemia. Therefore, we tested surface treatments on cyclic-olefin polymer-based microfluidic devices (COP-MD) to promote the immobilisation of collagen as a 3D matrix protein. Thus, we compared three surface treatments in COP devices for culturing human cardiac fibroblasts (HCF) embedded in collagen hydrogels. We determined the immobilisation efficiency of collagen hydrogel by quantifying the hydrogel transversal area within the devices at the studied time points. Altogether, our results indicated that surface modification with polyacrylic acid photografting (PAA-PG) of COP-MD is the most effective treatment to avoid the quick collapse of collagen hydrogels. As a proof-of-concept experiment, and taking advantage of the low-gas permeability properties of COP-MD, we studied the application of PAA-PG pre-treatment to generate a self-induced ischaemia model. Different necrotic core sizes were developed depending on initial HCF density seeding with no noticeable gel collapse. We conclude that PAA-PG allows long-term culture, gradient generation and necrotic core formation of contractile cell types such as myofibroblasts. This novel approach will pave the way for new relevant in vitro co-culture models where fibroblasts play a key role such as wound healing, tumour microenvironment and ischaemia within microfluidic devices.

A mechanobiological model for tumor spheroid evolution with application to glioblastoma: A continuum multiphysics approach.

BACKGROUND: Spheroids are in vitro quasi-spherical structures of cell aggregates, eventually cultured within a hydrogel matrix, that are used, among other applications, as a technological platform to investigate tumor formation and evolution. Several interesting features can be replicated using this methodology, such as cell communication mechanisms, the effect of gradients of nutrients, or the creation of realistic 3D biological structures. The main objective of this work is to link the spheroid evolution with the mechanical activity of cells, coupled with nutrient consumption and the subsequent cell dynamics. METHOD: We propose a continuum mechanobiological model which accounts for the most relevant phenomena that take place in tumor spheroid evolution under in vitro suspension, namely, nutrient diffusion in the spheroid, kinetics of cellular growth and death, and mechanical interactions among the cells. The model is qualitatively validated, after calibration of the model parameters, versus in vitro experiments of spheroids of different glioblastoma cell lines. RESULTS: Our model is able to explain in a novel way quite different setups, such as spheroid growth (up to six times the initial configuration for U-87 MG cell line) or shrinking (almost half of the initial configuration for U-251 MG cell line); as the result of the mechanical interplay of cells driven by cellular evolution. CONCLUSIONS: Glioblastoma tumor spheroid evolution is driven by mechanical interactions of the cell aggregate and the dynamical evolution of the cell population. All this information can be used to further investigate mechanistic effects in the evolution of tumors and their role in cancer disease.

In vitro biomimetic models for glioblastoma-a promising tool for drug response studies.

The poor response of glioblastoma to current treatment protocols is a consequence of its intrinsic drug resistance. Resistance to chemotherapy is primarily associated with considerable cellular heterogeneity, and plasticity of glioblastoma cells, alterations in gene expression, presence of specific tumor microenvironment conditions and blood-brain barrier. In an attempt to successfully overcome chemoresistance and better understand the biological behavior of glioblastoma, numerous tri-dimensional (3D) biomimetic models were developed in the past decade. These novel advanced models are able to better recapitulate the spatial organization of glioblastoma in a real time, therefore providing more realistic and reliable evidence to the response of glioblastoma to therapy. Moreover, these models enable the fine-tuning of different tumor microenvironment conditions and facilitate studies on the effects of the tumor microenvironment on glioblastoma chemoresistance. This review outlines current knowledge on the essence of glioblastoma chemoresistance and describes the progress achieved by 3D biomimetic models. Moreover, comprehensive literature assessment regarding the influence of 3D culturing and microenvironment mimicking on glioblastoma gene expression and biological behavior is also provided. The contribution of the blood-brain barrier as well as the blood-tumor barrier to glioblastoma chemoresistance is also reviewed from the perspective of 3D biomimetic models. Finally, the role of mathematical models in predicting 3D glioblastoma behavior and drug response is elaborated. In the future, technological innovations along with mathematical simulations should create reliable 3D biomimetic systems for glioblastoma research that should facilitate the identification and possibly application in preclinical drug testing and precision medicine.

SpheroidJ: An Open-Source Set of Tools for Spheroid Segmentation.

BACKGROUND AND OBJECTIVES: Spheroids are the most widely used 3D models for studying the effects of different micro-environmental characteristics on tumour behaviour, and for testing different preclinical and clinical treatments. In order to speed up the study of spheroids, imaging methods that automatically segment and measure spheroids are instrumental; and, several approaches for automatic segmentation of spheroid images exist in the literature. However, those methods fail to generalise to a diversity of experimental conditions. The aim of this work is the development of a set of tools for spheroid segmentation that works in a diversity of settings. METHODS: In this work, we have tackled the spheroid segmentation task by first developing a generic segmentation algorithm that can be easily adapted to different scenarios. This generic algorithm has been employed to reduce the burden of annotating a dataset of images that, in turn, has been employed to train several deep learning architectures for semantic segmentation. Both our generic algorithm and the constructed deep learning models have been tested with several datasets of spheroid images where the spheroids were grown under several experimental conditions, and the images acquired using different equipment. RESULTS: The developed generic algorithm can be particularised to different scenarios; however, those particular algorithms fail to generalise to different conditions. By contrast, the best deep learning model, constructed using the HRNet-Seg architecture, generalises properly to a diversity of scenarios. In order to facilitate the dissemination and use of our algorithms and models, we present SpheroidJ, a set of open-source tools for spheroid segmentation. CONCLUSIONS: In this work, we have developed an algorithm and trained several models for spheroid segmentation that can be employed with images acquired under different conditions. Thanks to this work, the analysis of spheroids acquired under different conditions will be more reliable and comparable; and, the developed tools will help to advance our understanding of tumour behaviour.

Mathematical formulation and parametric analysis of in vitro cell models in microfluidic devices: application to different stages of glioblastoma evolution.

In silico models and computer simulation are invaluable tools to better understand complex biological processes such as cancer evolution. However, the complexity of the biological environment, with many cell mechanisms in response to changing physical and chemical external stimuli, makes the associated mathematical models highly non-linear and multiparametric. One of the main problems of these models is the determination of the parameters' values, which are usually fitted for specific conditions, making the conclusions drawn difficult to generalise. We analyse here an important biological problem: the evolution of hypoxia-driven migratory structures in Glioblastoma Multiforme (GBM), the most aggressive and lethal primary brain tumour. We establish a mathematical model considering the interaction of the tumour cells with oxygen concentration in what is called the go or grow paradigm. We reproduce in this work three different experiments, showing the main GBM structures (pseudopalisade and necrotic core formation), only changing the initial and boundary conditions. We prove that it is possible to obtain versatile mathematical tools which, together with a sound parametric analysis, allow to explain complex biological phenomena. We show the utility of this hybrid "biomimetic in vitro-in silico" platform to help to elucidate the mechanisms involved in cancer processes, to better understand the role of the different phenomena, to test new scientific hypotheses and to design new data-driven experiments.

Author Correction: Enabling cell recovery from 3D cell culture microfluidic devices for tumour microenvironment biomarker profiling.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Enabling cell recovery from 3D cell culture microfluidic devices for tumour microenvironment biomarker profiling.

The tumour microenvironment (TME) has recently drawn much attention due to its profound impact on tumour development, drug resistance and patient outcome. There is an increasing interest in new therapies that target the TME. Nonetheless, most established in vitro models fail to include essential cues of the TME. Microfluidics can be used to reproduce the TME in vitro and hence provide valuable insight on tumour evolution and drug sensitivity. However, microfluidics remains far from well-established mainstream molecular and cell biology methods. Therefore, we have developed a quick and straightforward collagenase-based enzymatic method to recover cells embedded in a 3D hydrogel in a microfluidic device with no impact on cell viability. We demonstrate the validity of this method on two different cell lines in a TME microfluidic model. Cells were successfully retrieved with high viability, and we characterised the different cell death mechanisms via AMNIS image cytometry in our model.

Chemo-protective and regenerative effects of diarylheptanoids from the bark of black alder (Alnus glutinosa) in human normal keratinocytes.

Medicinal plants are recognized from ancient times as a source of diverse therapeutic agents and many of them are used as dietary supplements. Comprehensive approaches are needed that would identify bioactive components with evident activity against specific indications and provide a better link between science (ethno-botany, chemistry, biology and pharmacology) and market. Recently, the bark of black alder (Alnus glutinosa) appeared at market in the form of food supplement for treatment of different skin conditions. This study aimed to evaluate protective effects of two diarylheptanoids isolated from the bark of black alder: platyphylloside, 5(S)-1,7-di(4-hydroxyphenyl)-3-heptanone-5-O-ß-D-glucopyranoside (1) and its newly discovered analog 5(S)-1,7-di(4-hydroxyphenyl)-5-O-ß-D-[6-(E-p-coumaroylglucopyranosyl)]heptane-3-one (2) towards doxorubicin damaging activity. To that end, we employed HaCaT cells, non-cancerous human keratinocytes commonly used for skin regenerative studies. Diarylheptanoids significantly antagonized the effects of doxorubicin by lowering the sensitivity of HaCaT cells to this drug. Compound 2 prevented doxorubicin-induced cell death by activating autophagy. Both 1 and 2 protected HaCaT cells against doxorubicin-induced DNA damage. They significantly promoted migration and affected F-actin distribution. These results indicate that chemo-protective effects of diarylheptanoids may occur at multiple subcellular levels. Therefore, diarylheptanoids 1 and 2 could be considered as protective agents for non-cancerous dividing cells during chemotherapy.